2021-FEB-23

Mihi

  • Tihe mauri ora!
  • Ko (Uber) te waka
  • Ko (Chestnut Ridge
  • Ko (Niagra) te awa
  • Ko (Ameliká) te iwi
  • Ko (Bulbulia) te hapū
  • Ko (Joseph) ahau

Your trial by fire in R

Emotonal expressions as signals?

Dynamics?

Two years over the coals

What happened?

Topics

  1. Course basics
  2. Coding basics
  3. Graphs
  4. Consolidation of basic coding skills in R
  5. (non)Linear Regression with 1 x covariate/2 x covariates
  6. Confounding & causal dags
  1. Binary, count, ordinal data
  2. Multilevel models: group-level intercept
  3. Multilevel models: group-level slopes
  4. Timeseries data: within/between effects
  5. Measurement + missing data
  6. Bayesian inference/consolidation of statistics

Where to find material

Weekly lectures and course resources are located here

Problem sets are located at the end of each week’s lecture page.

Any readings will be linked in to the lecture page for the relevant day. If there are no readings that week we will specify: no readings

Journals

  • Weekly journal entries (about 100 - 200 words) (10 X journals = 10%)

  • These are due every Friday during term at midnight.

  • All submissions will be on Blackboard, but you may link the Blackboard submission to your GitHub page. (Not our rules!)

  • Format: document your insights, questions, and frustrations in a weekly journal.

  • This record should include how you have sought help to address your questions, and how you have offered help.

  • The purpose of the journals are to cultivate skills for interacting with the R community, and for documenting the research process.

Assements